{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "74adf2af",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Importing plotly failed. Interactive plots will not work.\n"
     ]
    }
   ],
   "source": [
    "# fix python path if working locally\n",
    "from utils import fix_pythonpath_if_working_locally\n",
    "fix_pythonpath_if_working_locally()\n",
    "\n",
    "from darts.models import TCNModel, RNNModel\n",
    "from darts.utils import timeseries_generation as tg\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e1b12ab6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[2021-06-22 11:42:11,491] INFO | darts.models.torch_forecasting_model | Train dataset contains 181 samples.\n",
      "[2021-06-22 11:42:11,491] INFO | darts.models.torch_forecasting_model | Train dataset contains 181 samples.\n",
      "[2021-06-22 11:42:11,497] INFO | darts.models.tcn_model | Number of layers chosen: 4\n",
      "[2021-06-22 11:42:11,497] INFO | darts.models.tcn_model | Number of layers chosen: 4\n",
      "[2021-06-22 11:42:15,337] INFO | darts.models.torch_forecasting_model | Train dataset contains 181 samples.\n",
      "[2021-06-22 11:42:15,337] INFO | darts.models.torch_forecasting_model | Train dataset contains 181 samples.\n",
      "[2021-06-22 11:42:15,341] INFO | darts.models.tcn_model | Number of layers chosen: 4\n",
      "[2021-06-22 11:42:15,341] INFO | darts.models.tcn_model | Number of layers chosen: 4\n"
     ]
    }
   ],
   "source": [
    "ts_length = 400\n",
    "split_ratio = 0.6\n",
    "sine_1_ts = tg.sine_timeseries(length=ts_length)\n",
    "sine_2_ts = tg.sine_timeseries(length=ts_length, value_frequency=0.05)\n",
    "sine_3_ts = tg.sine_timeseries(length=ts_length, value_frequency=0.003, value_amplitude=5)\n",
    "linear_ts = tg.linear_timeseries(length=ts_length, start_value=3, end_value=8)\n",
    "\n",
    "\n",
    "covariates = sine_3_ts.stack(sine_2_ts).stack(linear_ts)\n",
    "covariates_past, covariates_future = covariates.split_after(split_ratio)\n",
    "\n",
    "target = sine_1_ts + sine_2_ts + linear_ts + sine_3_ts\n",
    "target_past, target_future = target.split_after(split_ratio)\n",
    "model = TCNModel(input_chunk_length=50, output_chunk_length=10, n_epochs=100, random_state=0)\n",
    "\n",
    "model.fit(series=target_past)\n",
    "long_pred_no_cov = model.predict(n=160, series=[target_past, target_past[:60]])\n",
    "\n",
    "model = TCNModel(input_chunk_length=50, output_chunk_length=10, n_epochs=100, random_state=0)\n",
    "model.fit(series=target_past, covariates=covariates_past)\n",
    "long_pred_with_cov = model.predict(n=160, series=[target_past, target_past[:60], target_past[:80]], covariates=[covariates]*3, batch_size=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bb44ac2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f85ed24f3d0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "target.plot()\n",
    "long_pred_no_cov[0].plot(label='no-cov')\n",
    "long_pred_no_cov[1].plot(label='no-cov')\n",
    "long_pred_with_cov[1].plot(label='with-cov')\n",
    "long_pred_with_cov[0].plot(label='with-cov')\n",
    "long_pred_with_cov[2].plot(label='with-cov')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "03e43ad5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "32"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.batch_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e6a534a2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
